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User-Customized Password Speaker Verification based on HMM/ANN and GMM Models

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Hybrid HMM/ANN and GMM Combination for User-Customized Password Speaker Verification

Hervé Bourlard

Recently we have proposed an approach for user-customized password speaker verification; in this approach, we combined a hybrid HMM/ANN model (used for utterance verification) and a GMM model (used for speaker verification). In this paper, we extend our in ...

IDIAP2002

User Customized HMM/ANN Based Speaker Verification

Hervé Bourlard

In this paper, we describe a new speaker verification approach, using a hybrid HMM/ANN system, and accommodating user customized passwords. This system is exploiting the high phonetic recognition rates usually achieved by HMM/ANN speaker independent system ...

IDIAP2001

IDIAP HMM/HMM2 System: Theoretical Basis and Software Specifications

Hervé Bourlard, Samy Bengio, Katrin Weber, Shajith Ikbal

State-of-the-art Automatic Speech Recognition (ASR) systems make extensive use of Hidden Markov Models (HMMs), characterized by flexible statistical modeling, powerful optimization (training) techniques and efficient recognition algorithms. When allowed by ...

IDIAP2001

Mixed Bayesian Networks with Auxiliary Variables for Automatic Speech Recognition

Hervé Bourlard

Standard hidden Markov models (HMMs), as used in automatic speech recognition (ASR), calculate their emission probabilities by an artificial neural network (ANN) or a Gaussian distribution conditioned on the hidden state variable, considering the emissions ...

IDIAP2001

Pronunciation models and their evaluation using confidence measures

Hervé Bourlard

In this report, we present preliminary experiments towards automatic inference and evaluation of pronunciation models based on multiple utterances of each lexicon word and their given baseline pronunciation model (baseform phonetic transcription). In the p ...

IDIAP2001

MAP Combination of Multi-Stream HMM or HMM/ANN Experts

Hervé Bourlard, Astrid Hagen

Automatic speech recognition (ASR) performance falls dramatically with the level of mismatch between training and test data. The human ability to recognise speech when a large proportion of frequencies are dominated by noise has inspired the "missing data" ...

IDIAP2001

MAP Combination of Multi-Stream HMM or HMM/ANN Experts

Hervé Bourlard, Astrid Hagen

2001

Speechreading using Probabilistic Models

We describe a robust method for locating and tracking lips in gray-level image sequences. Our approach learns patterns of shape variability from a training set which constrains the model during image search to only deform in ways similar to the training ex ...

Academic Press1997

Speechreading using Probabilistic Models

IDIAP1997